Instructions to use tattabio/gLM2_150M_no_prune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tattabio/gLM2_150M_no_prune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tattabio/gLM2_150M_no_prune", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("tattabio/gLM2_150M_no_prune", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Card for Model ID
gLM2 150M development model trained without data pruning. See https://openreview.net/challenge?redirect=%2Fforum%3Fid%3DjlzNb1iWs3
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